Abstract
Synthetic aperture radar (SAR) is a widely used remote sensing observation technique. However, SAR raw echo data may be lost during the process of data acquisition by radar platform. In this paper, the imaging problem of SAR echo signal with periodically missing data along the azimuth is analyzed and a novel imaging method is proposed. Firstly, the problem of artificial artifact targets caused by periodically missing data is explained in detail, and the corresponding mathematical model is established. Then, the recovery method based on the RELAX algorithm with periodic notches data is proposed. In addition, when the size of two-dimensional (2D) echo data are large, block restoration along the azimuth is proposed to reduce the amount of calculation. Finally, the advantages of the algorithm proposed in this paper is demonstrated by the points target simulated SAR echo data processing and the real raw SAR echo data processing. When the azimuth periodically missing data rate is 50%, the SAR echo data can be recovered and the well-focused image can be obtained. Comparing the image entropy value and structural similarity index (SSIM) of the focused image, it proves the superiority of the proposed algorithm in solving the imaging problem of SAR azimuth periodically missing data.
Highlights
Synthetic Aperture Radar (SAR) is an important technology in modern remote sensing observation field
The artificial artifact targets and targets ambiguity caused by periodically missing data along the azimuth are analyzed at first
The method to reconstruct periodic notches data based on the RELAX algorithm is proposed
Summary
Synthetic Aperture Radar (SAR) is an important technology in modern remote sensing observation field. The compressed sensing SAR imaging using the accurate observation model has a large amount of computational complexity and it is suitable for SAR reconstruction imaging with a small size echo data. In [21], the sparse SAR imaging framework based on the approximate observation model is proposed This theoretical framework can directly reconstruct the image for large amount of SAR echo data. Under the condition that the observation targets are sparse, the methods used compressed sensing theory can effectively reconstruct targets image with the SAR echo signal missing data. Aiming at the shortage of periodically missing data SAR imaging by spectral estimation method and compressed sensing method, in this paper, the imaging method of SAR azimuth periodically continuous missing data based on the RELAX algorithm is proposed.
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